Performance Comparison of Surrogate-Assisted Evolutionary Algorithms on Computational Fluid Dynamics Problems

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26210%2F24%3APU155644" target="_blank" >RIV/00216305:26210/24:PU155644 - isvavai.cz</a>

Result on the web

<a href="https://link.springer.com/chapter/10.1007/978-3-031-70068-2_19" target="_blank" >https://link.springer.com/chapter/10.1007/978-3-031-70068-2_19</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/978-3-031-70068-2_19" target="_blank" >10.1007/978-3-031-70068-2_19</a>

Result language

angličtina

Original language name

Performance Comparison of Surrogate-Assisted Evolutionary Algorithms on Computational Fluid Dynamics Problems

Original language description

Surrogate-assisted evolutionary algorithms (SAEAs) are recently among the most widely studied methods for their capability to solve expensive real-world optimization problems. However, the development of new methods and benchmarking with other techniques still relies almost exclusively on artificially created problems. In this paper, we use two real-world computational fluid dynamics problems to compare the performance of eleven state-of-the-art single-objective SAEAs. We analyze the performance by investigating the quality and robustness of the obtained solutions and the convergence properties of the selected methods. Our findings suggest that the more recently published methods, as well as the techniques that utilize differential evolution as one of their optimization mechanisms, perform significantly better than the other considered methods.

Czech name

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Czech description

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Type

D - Article in proceedings

CEP classification

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OECD FORD branch

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Project

<a href="/en/project/GA24-12474S" target="_blank" >GA24-12474S: Benchmarking derivative-free global optimization methods</a><br>

Continuities

S - Specificky vyzkum na vysokych skolach

Publication year

2024

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection

18th International Conference on Parallel Problem Solving from Nature

ISBN

978-3-031-70068-2

ISSN

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e-ISSN

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Number of pages

19

Pages from-to

303-321

Publisher name

Springer Science and Business Media Deutschland GmbH

Place of publication

neuveden

Event location

Hagenberg, Austria

Event date

Sep 14, 2024

Type of event by nationality

WRD - Celosvětová akce

UT code for WoS article

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